Journal of Alzheimer's Disease - Volume 90, issue 4

Authors: Laton, Jorne | Van Schependom, Jeroen | Goossens, Joery | Wiels, Wietse | Sieben, Anne | De Deyn, Peter Paul | Goeman, Johan | Streffer, Johannes | van der Zee, Julie | Martin, Jean-Jacques | Van Broeckhoven, Christine | De Vos, Maarten | Bjerke, Maria | Nagels, Guy | Engelborghs, Sebastiaan

Article Type: Research Article

Abstract: Background: Distinguishing between Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD) results in poor diagnostic accuracy. Objective: To investigate the utility of electroencephalography (EEG)-based biomarkers in comparison and in addition to established cerebrospinal fluid (CSF) biomarkers in the AD versus FTLD differential diagnosis. Methods: The study cohort comprised 37 AD and 30 FTLD patients, of which 17 AD and 9 FTLD patients had definite diagnoses. All participants had CSF neurochemical (NCM) biomarker analyses (Aβ1-42 , T-tau, P-tau181 , and Nf-L) and underwent 19-channel resting-state EEG. From the EEG spectra, dominant frequency peaks were extracted in four …regions resulting in four dominant frequencies. This produced eight features (4 NCM + 4 EEG). Results: When NCM and EEG markers were combined, the diagnostic accuracy increased significantly. In the whole group, the accuracy went up from 79% (NCM) to almost 82%, while in the definite group only, it went up from around 85% to almost 95%. Two differences in the occurrence of the dominant EEG frequency were discovered: people lacking a clear dominant peak almost all had definite AD, while people with two peaks more often had FTLD. Conclusion: Combining EEG with NCM biomarkers resulted in differential diagnostic accuracies of 82% in clinically diagnosed AD and FTD patients and of 95% in patients having a definite diagnosis, which was significantly better than with EEG or NCM biomarkers alone. This suggests that NCM and EEG markers are complementary, revealing different aspects of the disease and therefore confirms again their relevance in developing additional diagnosis tools. Show more

Keywords: Alzheimer’s disease, amyloid-β, cerebrospinal fluid, dementia, EEG, frontotemporal dementia, neurofilament light, random forest, tau protein

DOI: 10.3233/JAD-220693

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1739-1747, 2022

Authors: Ren, Shuhua | Hu, Jingchao | Huang, Lin | Li, Junpeng | Jiang, Donglang | Hua, Fengchun | Guan, Yihui | Guo, Qihao | Xie, Fang | Huang, Qi

Article Type: Research Article

Abstract: Background: Subjects with subjective cognitive decline (SCD) are proposed as a potential population to screen for Alzheimer’s disease (AD). Objective: Investigating brain topologies would help to mine the neuromechanisms of SCD and provide new insights into the pathogenesis of AD. Methods: Objectively cognitively unimpaired subjects from communities who underwent resting-state BOLD-fMRI and clinical assessments were included. The subjects were categorized into SCD and normal control (NC) groups according to whether they exhibited self-perceived cognitive decline and were worried about it. The minimum spanning tree (MST) of the functional brain network was calculated for each subject, based …on which the efficiency and centrality of the brain network organization were explored. Hippocampal/parahippocampal volumes were also detected to reveal whether the early neurodegeneration of AD could be seen in SCD. Results: A total of 49 subjects in NC and 95 subjects in SCD group were included in this study. We found the efficiency and centrality of brain network organization, as well as the hippocampal/parahippocampal volume were preserved in SCD. Besides, SCD exhibited normal cognitions, including memory, language, and execution, but increased depressive and anxious levels. Interestingly, language and execution, instead of memory, showed a significant positive correlation with the maximum betweenness centrality of the functional brain organization and hippocampal/parahippocampal volume. Neither depressive nor anxious scales exhibited correlations with the brain functional topologies or hippocampal/parahippocampal volume. Conclusion: SCD exhibited preserved efficiency and centrality of brain organization. In clinical practice, language and execution as well as depression and anxiety should be paid attention in SCD. Show more

Keywords: Alzheimer’s disease, functional brain topologies, hippocampal volume, minimum spanning tree, subjective cognitive decline

DOI: 10.3233/JAD-220527

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1749-1759, 2022

Authors: Ganapathi, Aarthi S. | Glatt, Ryan M. | Bookheimer, Tess H. | Popa, Emily S. | Ingemanson, Morgan L. | Richards, Casey J. | Hodes, John F. | Pierce, Kyron P. | Slyapich, Colby B. | Iqbal, Fatima | Mattinson, Jenna | Lampa, Melanie G. | Gill, Jaya M. | Tongson, Ynez M. | Wong, Claudia L. | Kim, Mihae | Porter, Verna R. | Kesari, Santosh | Meysami, Somayeh | Miller, Karen J. | Bramen, Jennifer E. | Merrill, David A. | Siddarth, Prabha

Article Type: Research Article

Abstract: Background: Distinguishing between subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia in a scalable, accessible way is important to promote earlier detection and intervention. Objective: We investigated diagnostic categorization using an FDA-cleared quantitative electroencephalographic/event-related potential (qEEG/ERP)-based cognitive testing system (eVox® by Evoke Neuroscience) combined with an automated volumetric magnetic resonance imaging (vMRI) tool (Neuroreader® by Brainreader). Methods: Patients who self-presented with memory complaints were assigned to a diagnostic category by dementia specialists based on clinical history, neurologic exam, neuropsychological testing, and laboratory results. In addition, qEEG/ERP (n  = 161) and quantitative vMRI (n … = 111) data were obtained. A multinomial logistic regression model was used to determine significant predictors of cognitive diagnostic category (SCD, MCI, or dementia) using all available qEEG/ERP features and MRI volumes as the independent variables and controlling for demographic variables. Area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the prediction models. Results: The qEEG/ERP measures of Reaction Time, Commission Errors, and P300b Amplitude were significant predictors (AUC = 0.79) of cognitive category. Diagnostic accuracy increased when volumetric MRI measures, specifically left temporal lobe volume, were added to the model (AUC = 0.87). Conclusion: This study demonstrates the potential of a primarily physiological diagnostic model for differentiating SCD, MCI, and dementia using qEEG/ERP-based cognitive testing, especially when combined with volumetric brain MRI. The accessibility of qEEG/ERP and vMRI means that these tools can be used as adjuncts to clinical assessments to help increase the diagnostic certainty of SCD, MCI, and dementia. Show more

Keywords: Dementia, electroencephalography, magnetic resonance imaging, mild cognitive impairment

DOI: 10.3233/JAD-220616

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1761-1769, 2022

Authors: Giraldo, Diana L. | Smith, Robert E. | Struyfs, Hanne | Niemantsverdriet, Ellis | De Roeck, Ellen | Bjerke, Maria | Engelborghs, Sebastiaan | Romero, Eduardo | Sijbers, Jan | Jeurissen, Ben

Article Type: Research Article

Abstract: Background: Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer’s disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. Objective: In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and …controls. Methods: By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. Results: Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. Conclusion: This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset. Show more

Keywords: Alzheimer’s disease, cerebrospinal fluid, cognitive dysfunction, dementia, diffusion MRI, gray matter, white matter

DOI: 10.3233/JAD-220551

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022

Authors: Gaubert, Fanny | Borg, Céline | Chainay, Hanna

Article Type: Research Article

Abstract: Background: Alzheimer’s disease (AD) negatively impacts patients’ ability to make advantageous decisions, i.e., a core ability contributing to the preservation of autonomy. Objective: The present study aims to analyze the changes that occur in the decision-making competence (DMC) in AD patients and to determine if these changes are related to the deterioration of executive functions and working memory. Method: To this end, 20 patients with AD and 20 elderly control adults were assessed using executive, working memory, and DMC tasks. The latter comprised the Iowa Gambling Task (IGT) and a scenarios task based on situations inspired …by everyday life and performed under conditions of risk and ambiguity. Results: Results revealed lower performances in AD patients than in elderly control adults for all the tasks assessing cognitive functions. The AD patients also made more strategy changes during the IGT. In the scenarios tasks, the two groups took as many ambiguous or risky decisions, but AD patients tended to take more risks in the context of gain than elderly control adults did. Switching and updating ability, as well as working memory, appeared to be involved in decisions in tasks inspired by everyday life, while inhibition was more related to the IGT performances. Conclusion: Working memory and executive functions seem to be involved in decision-making, but in different ways in gambling and daily-life situations. Show more

Keywords: Alzheimer’s disease, decision making, executive function, working memory

DOI: 10.3233/JAD-220581

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1793-1815, 2022

Authors: Kleiman, Michael J. | Chang, Lun-Ching | Galvin, James E.

Article Type: Research Article

Abstract: Background: It is difficult to assess brain health status and risk of cognitive impairment, particularly at the initial evaluation. To address this, we developed the Brain Health Platform to quantify brain health and identify Alzheimer’s disease and related disorders (ADRD) risk factors by combining a measure of brain health: the Resilience Index (RI), a measure of risk of ADRD; the Vulnerability Index (VI); and the Number-Symbol Coding Task (NSCT), a measure of brain performance. Objective: The Brain Health Platform is intended to be easily and quickly administered, providing an overview of a patient’s risk of developing future impairment …based on modifiable and non-modifiable factors as well as current cognitive performance. Methods: This cross-sectional study comprehensively evaluated 230 participants (71 controls, 71 mild cognitive impairment, 88 ADRD). VI and RI scores were derived from physical assessments, lifestyle questionnaires, demographics, medical history, and neuropsychological examination including the NSCT. Results: Individuals with abnormal scores were 95.7% likely to be impaired, with a misclassification rate of 9.7%. The combined model had excellent discrimination (AUC:0.923±0.053; p  < 0.001), performing better than the Montreal Cognitive Assessment. Conclusion: The Brain Health Platform combines measures of resilience, vulnerability, and performance to provide a cross-sectional snapshot of overall brain health. The Brain Health Platform can effectively and accurately identify even the very mildest impairments due to ADRD, leveraging brief yet powerful and actionable indices of brain health and risk that could be used to develop personalized, precision medicine-like interventions. Show more

Keywords: Alzheimer’s disease, brain health, cognitive assessment, dementia, dementia with Lewy bodies, mild cognitive impairment, resilience, screening, vascular cognitive impairment, vulnerability

DOI: 10.3233/JAD-220927

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1817-1830, 2022

Authors: Whitehouse, Peter J. | George, Daniel R.

Article Type: Book Review

DOI: 10.3233/JAD-221066

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1831-1833, 2022

Article Type: Other

DOI: 10.3233/JAD-229012

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1835-1849, 2022

Authors: Prema, Asokan | Justin Thenmozhi, Arokiasamy | Manivasagam, Thamilarasan | Mohamed Essa, Musthafa | Guillemin, Gilles J.

Article Type: Correction

DOI: 10.3233/JAD-229017

Citation: Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1851-1852, 2022